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    %% Estimate Out-of-Bag Quantile Regression Error
%%
% Load the |carsmall| data set.  Consider a model that predicts the fuel
% economy of a car given its engine displacement, weight, and number of
% cylinders.  Consider |Cylinders| a categorical variable.
load carsmall
Cylinders = categorical(Cylinders);
X = table(Displacement,Weight,Cylinders,MPG);
%%
% Train an ensemble of bagged regression trees using the entire data set.
% Specify 100 weak learners and save the out-of-bag indices.
rng(1); % For reproducibility
Mdl = TreeBagger(100,X,'MPG','Method','regression','OOBPrediction','on');
%%
% |Mdl| is a |TreeBagger| ensemble.
%%
% Perform quantile regression, and out-of-bag estimate the MAD of the
% entire ensemble using the predicted conditional medians.
oobErr = oobQuantileError(Mdl)
%%
% |oobErr| is an unbiased estimate of the quantile regression error for the
% entire ensemble.